Reducing Diabetes with AI: Leveraging Healthcare Data and Ensuring Patient Privacy

Sudheer Kumar Lagisetty

Abstract: In today's healthcare landscape, Artificial Intelligence (AI) presents transformative opportunities for diabetes prevention and management by leveraging insights from diverse data sources, including electronic health records and insurance claims. This paper explores how AI algorithms can analyze these data points to predict diabetes risk, enabling healthcare providers to deploy precision-targeted, preventative interventions. While practical data access may vary, this study emphasizes the responsible integration of AI within healthcare systems, where rigorous practices such as data anonymization, pseudonymization, and secure processing are paramount in protecting patient privacy. By discussing best practices for implementing AI-driven solutions within existing healthcare frameworks, this paper outlines a vision for AI that enhances patient outcomes, streamlines resource use, and reduces costs without compromising ethical standards. Through a privacy-first, data-centric approach, AI can create new pathways for proactive, efficient diabetes care within a healthcare IT framework.

Keywords: Artificial Intelligence in healthcare, diabetes prevention, data privacy, predictive analytics, healthcare IT